A dependency-based method for evaluating broad-coverage parsers
Natural Language Engineering
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Non-projective dependency parsing using spanning tree algorithms
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Prepositional phrase attachment without oracles
Computational Linguistics
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Dependency parsers show syntactic relations between words using a directed graph, but comparing dependency parsers is difficult because of differences in theoretical models. We describe a system to convert dependency models to a structural grammar used in grammar education. Doing so highlights features that are potentially overlooked in the dependency graph, as well as exposing potential weaknesses and limitations in parsing models. Our system performs automated analysis of dependency relations and uses them to populate a data structure we designed to emulate sentence diagrams. This is done by mapping dependency relations between words to the relative positions of those words in a sentence diagram. Using an original metric for judging the accuracy of sentence diagrams, we achieve precision of 85%. Multiple causes for errors are presented as potential areas for improvement in dependency parsers.